ORCID Profile
0000-0001-8461-3717
Current Organisation
China University of Mining and Technology - Beijing Campus
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Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 05-07-2017
Publisher: Informa UK Limited
Date: 07-11-2017
DOI: 10.1080/10803548.2017.1372943
Abstract: Human and organizational factors have been proven to be the prime causes of Chinese hazardous chemical accidents (HCAs). A modified version of the Human Factors Analysis and Classification System (HFACS), namely the HFACS-Hazardous Chemicals (HC), was developed to identify the human factors involved in Chinese HCAs. The '8.12' Tianjin Port fire and explosion, the costliest HCA in recent years, was reanalyzed using this framework, and the results were compared with the official accident inquiry report to determine their differences related to the identification of human and organizational factors. The study revealed that interacting human factors from different levels in Ruihai Company led to this catastrophe, and the inquiry report had limitations in the identification of human factors and the guidance for similar accident prevention. This study showed the applicability of the HFACS-HC in HCA analyses as well as the necessity to recommend this approach for future HCA investigations.
Publisher: Inderscience Publishers
Date: 2014
Publisher: IOP Publishing
Date: 12-12-2018
Publisher: MDPI AG
Date: 02-02-2019
DOI: 10.3390/PR7020073
Abstract: In order to effectively prevent coal mine accidents, we selected the most serious type of accident in coal mines—gas explosions—as the research object. Based on the accident causation model (24Model), we propose an action path and analysis steps of accidents caused by different employees in the organization. A gas explosion coal mine accident was analyzed using the 24Model and the proposed action path, and 12 unsafe actions, 3 unsafe states, 4 habitual behaviors, 10 safety management systems, and 10 safety cultures were obtained. Case analysis results show that by using the 24Model and path analysis the proposed effect can help employees to clearly identify the cause of the accident, to better understand the logical relationship with the causes of the accident, improve the effectiveness of training, and effectively prevent similar accidents. The 24Model and the proposed path can be used to comprehensively analyze the reasons for and help to effectively prevent coal mine gas explosion accidents.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Wiley
Date: 26-07-2016
DOI: 10.1002/PRS.11837
Publisher: Informa UK Limited
Date: 22-06-2020
Publisher: SAGE Publications
Date: 17-05-2022
DOI: 10.1177/1748006X221099094
Abstract: The Swiss Cheese Model (SCM) and 24Model have proved over the years to be lasting influences for many researchers and practitioners in various safety areas. However, as one practical tool for accident analysis, a gap still exists for whether these two models are consistent in current studies. A theoretical comparison of these two models to reveal constructive foundation, related concepts, correspondence to each level of cause-effect and characteristics of sub modules were presented. The basic structure of the two modular models is consistent and each sub module can match. The foundation of the two models is different, reflecting the differences between Eastern and Western cultures. 24Model overcomes the fuzziness of SCM model classification and ides organizational factors into two stages: safety management system and safety culture and refines the meaning of accident and hazard. Hazard identification based on SCM is presented at the design and commissioning of the system, while the identification of 24Model following PDCA cycle, which is an continuous improvement throughout the entire life cycle of the system. In conclusion, 24Model is a deepening and development of SCM, and explicit taxonomy for in idual and organization is proposed by integrating factors on SCM. The comparisons will build a bridge of communication and exchange between East and West accident causation theories and will lead to more knowledge of the causes to the accident, placing focus on need for improved organizational behaviors, more efficient safety management systems and safety culture in companies.
Publisher: Elsevier BV
Date: 02-2017
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 02-2017
Publisher: Elsevier BV
Date: 02-2018
Publisher: Wiley
Date: 24-02-2019
DOI: 10.1002/PRS.12044
Publisher: Elsevier BV
Date: 06-2013
DOI: 10.1016/J.JSR.2013.01.001
Abstract: This study develops an integrative model of safety management based on social cognitive theory and the total safety culture triadic framework. The purpose of the model is to reveal the causal linkages between a hazardous environment, safety climate, and in idual safety behaviors. Based on primary survey data from 209 front-line workers in one of the largest state-owned coal mining corporations in China, the model is tested using structural equation modeling techniques. An employee's perception of a hazardous environment is found to have a statistically significant impact on employee safety behaviors through a psychological process mediated by the perception of management commitment to safety and in idual beliefs about safety. The integrative model developed here leads to a comprehensive solution that takes into consideration the environmental, organizational and employees' psychological and behavioral aspects of safety management.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Elsevier BV
Date: 07-2021
Publisher: Wiley
Date: 04-04-2022
DOI: 10.1002/HPJA.485
Abstract: National smoking prevalence is decreasing among Aboriginal and Torres Strait Islander people. In remote areas, Aboriginal and Torres Strait Islander smoking prevalence remains higher than in nonremote areas and is not improving. We analysed data from 539 daily and weekly smokers from remote areas who completed baseline surveys at either Wave 1 (April 2012‐October 2013) or Wave 2 (August 2013‐August 2014), including 157 from Wave 1 who also completed Wave 2, from the Talking About The Smokes project. We assessed associations between baseline predictor measures and having made any quit attempt in the past year and, among those who did, having sustained the last quit attempt for one month or more. More smokers had made a quit attempt if they were younger or reported being unable to buy essentials due to money spent on smokes, being more stressed, having several pro‐quitting motivations and attitudes, having an effective smoke‐free home, or being encouraged to quit by a health professional or by family/friends. Of these, more had sustained their last quit attempt for one month or more if they reported being more socially advantaged, no smoking‐induced deprivation, being less dependent, chewing pituri or an having effective smoke‐free home. Health staff should consider the quite different factors associated with starting and then sustaining a quit attempt. Our findings support continued attention in remote areas on smoke‐free homes and health staff providing regular encouragement to all smokers to quit and more use of smokers' friends and family for support.
Publisher: Informa UK Limited
Date: 30-07-2015
Publisher: Elsevier BV
Date: 07-2023
Publisher: Informa UK Limited
Date: 07-11-2017
DOI: 10.1080/10803548.2017.1372943
Abstract: Human and organizational factors have been proven to be the prime causes of Chinese hazardous chemical accidents (HCAs). A modified version of the Human Factors Analysis and Classification System (HFACS), namely the HFACS-Hazardous Chemicals (HC), was developed to identify the human factors involved in Chinese HCAs. The '8.12' Tianjin Port fire and explosion, the costliest HCA in recent years, was reanalyzed using this framework, and the results were compared with the official accident inquiry report to determine their differences related to the identification of human and organizational factors. The study revealed that interacting human factors from different levels in Ruihai Company led to this catastrophe, and the inquiry report had limitations in the identification of human factors and the guidance for similar accident prevention. This study showed the applicability of the HFACS-HC in HCA analyses as well as the necessity to recommend this approach for future HCA investigations.
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.JSR.2018.09.008
Abstract: Currently, there is a lack of specific analytical tools for general aviation accidents (GAAs). This has led to loopholes in the prevention of GAAs. A Swiss Cheese model for general aviation (SCM-GA) is proposed to identify the human and organizational factors involved in GAAs. In the proposed SCM-GA, 5 categories, 45 subcategories, a general aviation safety management system (GA-SMS) and safety culture were developed based on the classic accident causation models combined with the laws and regulations and safety management practices in the general aviation industry. One GAA was analyzed using SCM-GA. The human and organizational causes revealed by SCM-GA were more complete than the causes revealed through the accident report. The identification results of the deficiencies in the subcategories of GA-SMS and the safety culture were more consistent with the requirements in the general aviation laws and regulations than the organizational factors in the accident report. Based on the subcategories of SCM-GA, 41 GAAs that occurred between 1996 and 2010 in China were statistically analyzed and χ SCM-GA is an accident analysis tool that can comprehensively analyze the human and organizational deficiencies involved in GAAs. The accident causes revealed by SCM-GA were more consistent with the general aviation safety management practices. General aviation companies should establish their own GA-SMS and safety culture based on the subcategories developed herein. Using SCM-GA for routine safety inspection and accident investigation will help the management and the staff make effective safety decisions to effectively prevent GAAs.
Publisher: Informa UK Limited
Date: 21-07-2020
Publisher: Elsevier BV
Date: 06-2022
Location: China
Location: Australia
Start Date: 2016
End Date: 2020
Funder: National Natural Science Foundation of China
View Funded Activity